The Ariel Space Mission aims to observe a diverse sample of exoplanet atmospheres across a wide wavelength range of 0.5 to 7.8 microns. The observations are organized into four Tiers, with Tier 1 being a reconnaissance survey. This Tier is designed to achieve a sufficient signal-to-noise ratio (S/N) at low spectral resolution in order to identify featureless spectra or detect key molecular species without necessarily constraining their abundances with high confidence. We introduce a P-statistic that uses the abundance posteriors from a spectral retrieval to infer the probability of a molecule’s presence in a given planet’s atmosphere in Tier 1. We find that this method predicts probabilities that correlate well with the input abundances, indicating considerable predictive power when retrieval models have comparable or higher complexity compared to the data. However, we also demonstrate that the P-statistic loses representativity when the retrieval model has lower complexity, expressed as the inclusion of fewer than the expected molecules. The reliability and predictive power of the P-statistic are assessed on a simulated population of exoplanets with H2-He dominated atmospheres, and forecasting biases are studied and found not to adversely affect the classification of the survey.

Detecting molecules in Ariel low resolution transmission spectra / Bocchieri, Andrea; Mugnai, Lorenzo V.; Pascale, Enzo; Changeat, Quentin; Tinetti, Giovanna. - In: EXPERIMENTAL ASTRONOMY. - ISSN 0922-6435. - 56:(2023), pp. 605-644. [10.1007/s10686-023-09911-x]

Detecting molecules in Ariel low resolution transmission spectra

Andrea Bocchieri
Primo
;
Lorenzo V. Mugnai;Enzo Pascale;Giovanna Tinetti
2023

Abstract

The Ariel Space Mission aims to observe a diverse sample of exoplanet atmospheres across a wide wavelength range of 0.5 to 7.8 microns. The observations are organized into four Tiers, with Tier 1 being a reconnaissance survey. This Tier is designed to achieve a sufficient signal-to-noise ratio (S/N) at low spectral resolution in order to identify featureless spectra or detect key molecular species without necessarily constraining their abundances with high confidence. We introduce a P-statistic that uses the abundance posteriors from a spectral retrieval to infer the probability of a molecule’s presence in a given planet’s atmosphere in Tier 1. We find that this method predicts probabilities that correlate well with the input abundances, indicating considerable predictive power when retrieval models have comparable or higher complexity compared to the data. However, we also demonstrate that the P-statistic loses representativity when the retrieval model has lower complexity, expressed as the inclusion of fewer than the expected molecules. The reliability and predictive power of the P-statistic are assessed on a simulated population of exoplanets with H2-He dominated atmospheres, and forecasting biases are studied and found not to adversely affect the classification of the survey.
2023
methods data analysis; planets and satellites atmospheres; surveys; techniques spectroscopic
01 Pubblicazione su rivista::01a Articolo in rivista
Detecting molecules in Ariel low resolution transmission spectra / Bocchieri, Andrea; Mugnai, Lorenzo V.; Pascale, Enzo; Changeat, Quentin; Tinetti, Giovanna. - In: EXPERIMENTAL ASTRONOMY. - ISSN 0922-6435. - 56:(2023), pp. 605-644. [10.1007/s10686-023-09911-x]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1688015
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